Research presents the design and construction of a prototype device alert to clean the solar panels. The measure monitoring of dust and blocking dirt surface of solar panel causes generation Energy low efficiency the devices are alerted to clean solar panel to ensure generation Energy highest efficiency and reduce the cost of solar cell cleaning which will be done 12 times a year. Researchers have introduced electrical and electronic technology with solar panels to provide a reference. Take an installed prototype in process with solar panel energy factory. After that clean the panel referred to the morning every day. This prototype will be processing performance comparison between the solar panels reference with the solar panels factory every day and results via the Internet and record the data in memory. The results of this research found that. Efficiency of electricity production is down 9% as 3 months and 10.47% of the year due to impurities. Dust cover doing have been cleaned twice the efficiency of the electricity production has remained high. This will alert you that washing does not have to be done 12 times as practiced in a solar farm reducing costs 10 times a year.

The Purposes of this study were 1) to study the efficiency of childcentered approach in the faculty of mass Communication Technology Rajamangala Unuversity of Technology Phra Nakhon 2) to compare personal factors with attitude towards the efficiency of child-centeres approach in the Faculty of Mass Communication TechnologyRajamangala Unuversity of Technology Phra Nakhon 3) to study the progress of learning efficiency after the application of child-centered approach in the Faculty of Mass Communication Technology Rajamangala Unuversity of Technology Phra Nakhon and 4) to study the predicted variablesvariablespersonal factors:genderstudy areasstudent gradeschool record and attitudes towards child-centered approach. The sample taken for the investigation was a number of 300 students in academic year 2009 from the faculty of Mass Communication TechnologyRMUTP. The proportion of 300 students was considered as 50 % of all students studying in the semester 2/2009. The data were collected by questionnaires. The data were analyzed by frequency distributionpercentagemeanstandard deviationt-testF-test One-Way ANOVA and Stepwise multiple regression analysis.